Tracking data access in a dispersed storage network

ABSTRACT

A method for execution by a dispersed storage and task (DST) processing unit that includes a processor includes receiving an access request from a requesting entity via a network indicating an original data object. At least one read request is generated for transmission to at least one storage unit indicating a plurality of encoded original data slices associated with the original data object. A regenerated original data object is generated by utilizing a decoding scheme on the plurality of encoded original data slice. A transformed data object is generated for transmission to the requesting entity via the network by utilizing a transformation function on the first regenerated original data object based on an entity identifier associated with the requesting entity.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention; and

FIG. 10 is a logic diagram of an example of a method of tracking dataaccess in accordance with the present invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

In various embodiments, each of the storage units operates as adistributed storage and task (DST) execution unit, and is operable tostore dispersed error encoded data and/or to execute, in a distributedmanner, one or more tasks on data. The tasks may be a simple function(e.g., a mathematical function, a logic function, an identify function,a find function, a search engine function, a replace function, etc.), acomplex function (e.g., compression, human and/or computer languagetranslation, text-to-voice conversion, voice-to-text conversion, etc.),multiple simple and/or complex functions, one or more algorithms, one ormore applications, etc. Hereafter, a storage unit may be interchangeablyreferred to as a DST execution unit and a set of storage units may beinterchangeably referred to as a set of DST execution units.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each managing unit 18 and the integrity processing unit 20 maybe separate computing devices, may be a common computing device, and/ormay be integrated into one or more of the computing devices 12-16 and/orinto one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-8. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN memory 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), interne small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. Here, the computing device stores data object40, which can include a file (e.g., text, video, audio, etc.), or otherdata arrangement. The dispersed storage error encoding parametersinclude an encoding function (e.g., information dispersal algorithm,Reed-Solomon, Cauchy Reed-Solomon, systematic encoding, non-systematicencoding, on-line codes, etc.), a data segmenting protocol (e.g., datasegment size, fixed, variable, etc.), and per data segment encodingvalues. The per data segment encoding values include a total, or pillarwidth, number (T) of encoded data slices per encoding of a data segmenti.e., in a set of encoded data slices); a decode threshold number (D) ofencoded data slices of a set of encoded data slices that are needed torecover the data segment; a read threshold number (R) of encoded dataslices to indicate a number of encoded data slices per set to be readfrom storage for decoding of the data segment; and/or a write thresholdnumber (W) to indicate a number of encoded data slices per set that mustbe accurately stored before the encoded data segment is deemed to havebeen properly stored. The dispersed storage error encoding parametersmay further include slicing information (e.g., the number of encodeddata slices that will be created for each data segment) and/or slicesecurity information (e.g., per encoded data slice encryption,compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides dataobject 40 into a plurality of fixed sized data segments (e.g., 1 throughY of a fixed size in range of Kilo-bytes to Tera-bytes or more). Thenumber of data segments created is dependent of the size of the data andthe data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 80 is shown inFIG. 6. As shown, the slice name (SN) 80 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a schematic block diagram of another embodiment of a dispersedstorage network (DSN) that includes a computing device 16 of FIG. 1, thenetwork 24 of FIG. 1, a requesting entity 910, a verifying entity 920,and a plurality of storage units 1-n. Each computing device 16 caninclude the interface 32 of FIG. 1, the computing core 26 of FIG. 1, andthe DS client module 34 of FIG. 1. The computing device 16 can functionas a dispersed storage processing agent for computing device 14 asdescribed previously, and may hereafter be referred to as a distributedstorage and task (DST) processing unit. Each storage unit can include DSclient module 34 and may be implemented utilizing the storage unit 36 ofFIG. 1. The requesting entity 910 and/or verifying entity 920 may beimplemented utilizing computing devices 12-16 of FIG. 1. The DSNfunctions to track data access.

In the case where sensitive information is communicated to a trusted setof entities and accountability for keeping information confidential iscritical, the distributor of such information may desire the ability toidentify the entity who leaked information in the event of a securitybreach or data exposure. To achieve this, content is stored in a DSNmemory. To enable accountability for this content, a uniquetransformation is applied to data object upon access by an entity totrack that the entity accessed the content. For example, a requestingentity can request access to a data object stored in a DSN via acomputing device 12-16. The DST processing unit, upon receiving therequest indicating the data object, can retrieve the data object byretrieving a decode threshold number of encoded data slices associatedwith the data object from at least one storage unit of the DSN, andapplying the appropriate decoding function according to the dispersederror encoding scheme used. After recovering the data object, the DSTprocessing unit can apply a transformation function to the data objectbased on an identifier associated with the requesting entity. Thetransformed data object is returned to the requesting entity, andcontains a unique signature indicating that the data object has beenaccessed by the requesting entity.

In various embodiments, the transformed data object is also stored inthe DSN. For example, the DST processing unit can generate dispersederror encoded slices corresponding to the transformed object to bewritten to at least one storage unit. In various embodiments, the DSTprocessing unit can also request that the original data object beremoved from storage, or be replaced by the slices corresponding to thetransformed data object.

In various embodiments, the transformation function applies randomizedor pseudorandomized changes to the underlying stored content of the dataobject. In particular, in the case of content that can be lossilyencoded (such as a picture, sound file, video stream, document, etc.),imperceptible changes can be applied that are indistinguishable to thehuman senses. Furthermore, in various embodiments, the changesintroduced by the transformation function are great enough that theywould survive in any other copy of the content. For example, in the caseof an image or video file, may insert small pixel artifacts, in the caseof a sound file, sub-audible tweaks may be embedded in the sound, in thecase of a document, subtle differences in spacing, punctuation,type-face, etc. may be applied. These changes, when compared to theoriginal, will represent a unique signature or “water mark” forwhichever entity accessed the data. In various embodiments, otherinformation regarding the access, such as a time stamp, access location,and/or changes applied by the entity can also be included in the uniquesignature. In various embodiments, the transformation function isnon-reversible, and the unique signature can only be recovered if theoriginal data object is available. For example, a comparison function,when applied to both the original data object and the transformed dataobject, can be used to recover the unique signature and thus determinethe access history of the data object.

In various embodiments, a verifying unit can compare an original dataobject and a transformed data object to determine one or more requestingentities that accessed the content. For example, a verifying unit cansend an access history request to the DST processing unit that indicatesor includes the data object. For example, the original data objectand/or the transformed data object can be included in the access historyrequest itself. In other embodiments, the original data object and/ortransformed data object can be indicated in the request with anidentifier, and can be retrieved from storage by the DST processingunit. In various embodiments, the DST processing unit can return astored, transformed data object for comparison by the verifying entityitself. In other embodiments, the DST processing unit can perform thecomparison function itself on the original data object and thetransformed data object, and can return the access history indicated bythe output of the function to the requesting entity.

In various embodiments, a requesting entity can request write a dataobject to storage. The DST processing unit, upon receiving the dataobject, can perform the transformation function before storing the dataobject. In various embodiments, the DST processing unit will write boththe original data object and transformed data object to storage, forexample, for ease of comparison in the future. A verifying entity canretrieve the access history as usual and determine the data object waswritten by the requesting entity. In various embodiments, the accesshistory indicated in the unique signature will indicate that the dataobject was written by the requesting entity, while other uniquesignatures will indicate that a data object was merely read by arequesting entity.

In various embodiments, a data object can be accessed by multipleentities, and the access by multiple entities can be tracked via theunique signature. For example, after a first entity accesses a dataobject, the data object will be transformed based on an identifierassociated with the first entity, and the transformed data object can bereturned to the first accessing entity and can replace the original dataobject in storage. When a second entity requests the data object, thetransformation function will be applied to the already transformed dataobject, this time based on an identifier of the second entity. Thetransformed data object will now reflect the access history by both thefirst entity and the second entity, for example, when compared to theoriginal data object.

In various embodiments, a processing system of a dispersed storage andtask (DST) processing unit includes at least one processor and a memorythat stores operational instructions, that when executed by the at leastone processor cause the processing system to receive an access requestfrom a first requesting entity via a network indicating a first originaldata object. A first at least one read request is generated fortransmission to at least one storage unit indicating a plurality ofencoded original data slices associated with the first original dataobject. A first regenerated original data object is generated byutilizing a decoding scheme on the plurality of encoded original dataslices. A first transformed data object is generated for transmission tothe first requesting entity via the network by utilizing atransformation function on the first regenerated original data objectbased on a first entity identifier associated with the first requestingentity.

In various embodiments, the transformation function includes insertingrandomized and/or pseudorandomized changes to content of the firstoriginal data object. In various embodiments, the transformationfunction is a one-way function. In various embodiments, the firsttransformed data object includes new content that is generated byapplying imperceptible changes to content of the first original dataobject, i.e. where the new content of the first transformed data objectis indistinguishable from the content of the first original data objectby human senses. In various embodiments, the first original data objectincludes at least one of: image file content or video file content, andwhere generating the first transformed data object includes applyingchanges to at least one pixel of the at least one of: the image filecontent or the video file content. In various embodiments, the firstoriginal data object includes sound file content, and where generatingthe first transformed data object includes applying audible changes tothe sound file content. In various embodiments, the first original dataobject includes document file content, and where generating the firsttransformed data object includes applying changes to at least one of:spacing, punctuation, or type-face of the document file content.

In various embodiments, an access history request is received from averifying entity via the network that indicates the first original dataobject and includes the first transformed data object. A second at leastone read request is generated for transmission to at least one storageunit indicating the plurality of encoded original data slices associatedwith the first original data object. A second regenerated data object isgenerated by utilizing the decoding scheme on the plurality of encodedoriginal data slices. Access history data is generated based oncomparing the first transformed data object received from the verifyingentity to the second regenerated data object, where the access historydata indicates the first entity identifier associated with the firstrequesting entity. The first entity identifier is transmitted to theverifying entity via the network.

In various embodiments, a plurality of encoded transformed data slicesare generated by applying an encoding scheme to the first transformeddata object. A plurality of write requests are generated fortransmission to a first plurality of storage units via the network,where each of the plurality of write requests includes at least one ofthe plurality of encoded transformed data slices for storage. In variousembodiments, a plurality of delete requests corresponding to each of theplurality of encoded original data slices associated with the firstoriginal data object are generated for transmission to a secondplurality of storage units via the network, where each of the pluralityof delete requests indicate one of the plurality of encoded originaldata slices for removal from a corresponding one of the second pluralityof storage units. In various embodiments, each of the plurality of writerequests includes a request to replace one of the plurality of encodedoriginal data slices with a one of the plurality of encoded transformeddata slices. In various embodiments, an access history request isreceived from a verifying entity via the network that indicates thefirst original data object. A second at least one read request isgenerated for transmission to at least one of the first plurality ofstorage units indicating the plurality of encoded transformed dataslices associated with the first transformed data object. A regeneratedtransformed data object is generated by utilizing the decoding scheme onthe plurality of encoded transformed data slices. Access history data isgenerated based on comparing the first original data object to theregenerated transformed data object, where the access history dataindicates the first entity identifier associated with the firstrequesting entity. The first entity identifier is transmitted to theverifying entity via the network.

In various embodiments, a second original data object is received from asecond requesting entity for storage. A second transformed data objectis generated by utilizing the transformation function on the secondoriginal data object based on a second entity identifier associated withthe second requesting entity. A plurality of encoded transformed dataslices are generated by applying an encoding scheme to the secondtransformed data object. A plurality of write requests are generated fortransmission to a plurality of storage units via the network, where eachof the plurality of write requests includes at least one of theplurality of encoded transformed data slices for storage.

FIG. 10 is a flowchart illustrating an example of tracking data access.In particular, a method is presented for use in conjunction with one ormore functions and features described in association with FIGS. 1-9, forexecution by a dispersed storage and task (DST) processing unit thatincludes a processor or via another processing system of a dispersedstorage network that includes at least one processor and memory thatstores instruction that configure the processor or processors to performthe steps described below. Step 1002 includes receiving an accessrequest from a requesting entity via a network indicating an originaldata object. Step 1004 includes generating a first at least one readrequest for transmission to at least one storage unit indicating aplurality of encoded original data slices associated with the firstoriginal data object. Step 1006 includes generating a first regeneratedoriginal data object by utilizing a decoding scheme on the plurality ofencoded original data slices. Step 1008 includes generating a firsttransformed data object for transmission to the first requesting entityvia the network by utilizing a transformation function on the firstregenerated original data object based on a first entity identifierassociated with the first requesting entity.

In various embodiments, the transformation function includes insertingrandomized and/or pseudorandomized changes to content of the firstoriginal data object. In various embodiments, the transformationfunction is a one-way function. In various embodiments, the firsttransformed data object includes new content that is generated byapplying imperceptible changes to content of the first original dataobject, i.e. where the new content of the first transformed data objectis indistinguishable from the content of the first original data objectby human senses. In various embodiments, the first original data objectincludes at least one of: image file content or video file content, andwhere generating the first transformed data object includes applyingchanges to at least one pixel of the at least one of: the image filecontent or the video file content. In various embodiments, the firstoriginal data object includes sound file content, and where generatingthe first transformed data object includes applying audible changes tothe sound file content. In various embodiments, the first original dataobject includes document file content, and where generating the firsttransformed data object includes applying changes to at least one of:spacing, punctuation, or type-face of the document file content.

In various embodiments, an access history request is received from averifying entity via the network that indicates the first original dataobject and includes the first transformed data object. A second at leastone read request is generated for transmission to at least one storageunit indicating the plurality of encoded original data slices associatedwith the first original data object. A second regenerated data object isgenerated by utilizing the decoding scheme on the plurality of encodedoriginal data slices. Access history data is generated based oncomparing the first transformed data object received from the verifyingentity to the second regenerated data object, where the access historydata indicates the first entity identifier associated with the firstrequesting entity. The first entity identifier is transmitted to theverifying entity via the network.

In various embodiments, a plurality of encoded transformed data slicesare generated by applying an encoding scheme to the first transformeddata object. A plurality of write requests are generated fortransmission to a first plurality of storage units via the network,where each of the plurality of write requests includes at least one ofthe plurality of encoded transformed data slices for storage. In variousembodiments, a plurality of delete requests corresponding to each of theplurality of encoded original data slices associated with the firstoriginal data object are generated for transmission to a secondplurality of storage units via the network, where each of the pluralityof delete requests indicate one of the plurality of encoded originaldata slices for removal from a corresponding one of the second pluralityof storage units. In various embodiments, each of the plurality of writerequests includes a request to replace one of the plurality of encodedoriginal data slices with a one of the plurality of encoded transformeddata slices. In various embodiments, an access history request isreceived from a verifying entity via the network that indicates thefirst original data object. A second at least one read request isgenerated for transmission to at least one of the first plurality ofstorage units indicating the plurality of encoded transformed dataslices associated with the first transformed data object. A regeneratedtransformed data object is generated by utilizing the decoding scheme onthe plurality of encoded transformed data slices. Access history data isgenerated based on comparing the first original data object to theregenerated transformed data object, where the access history dataindicates the first entity identifier associated with the firstrequesting entity. The first entity identifier is transmitted to theverifying entity via the network.

In various embodiments, a second original data object is received from asecond requesting entity for storage. A second transformed data objectis generated by utilizing the transformation function on the secondoriginal data object based on a second entity identifier associated withthe second requesting entity. A plurality of encoded transformed dataslices are generated by applying an encoding scheme to the secondtransformed data object. A plurality of write requests are generated fortransmission to a plurality of storage units via the network, where eachof the plurality of write requests includes at least one of theplurality of encoded transformed data slices for storage.

In various embodiments, a non-transitory computer readable storagemedium includes at least one memory section that stores operationalinstructions that, when executed by a processing system of a dispersedstorage network (DSN) that includes a processor and a memory, causes theprocessing system to receiving an access request from a first requestingentity via a network indicating a first original data object. A first atleast one read request is generated for transmission to at least onestorage unit indicating a plurality of encoded original data slicesassociated with the first original data object. A first regeneratedoriginal data object is generated by utilizing a decoding scheme on theplurality of encoded original data slices. A first transformed dataobject is generated for transmission to the first requesting entity viathe network by utilizing a transformation function on the firstregenerated original data object based on a first entity identifierassociated with the first requesting entity.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by a dispersed storage andtask (DST) processing unit that includes a processor, the methodcomprises: receiving an access request from a first requesting entityvia a network indicating a first original data object; generating afirst at least one read request for transmission to at least one storageunit to retrieve a plurality of encoded original data slices associatedwith the first original data object; generating a first regeneratedoriginal data object by utilizing a decoding scheme on the plurality ofencoded original data slices; and generating a first transformed dataobject for transmission to the first requesting entity via the networkby utilizing a transformation function on the first regenerated originaldata object based on a first entity identifier associated with the firstrequesting entity.
 2. The method of claim 1, wherein the transformationfunction includes inserting one of: randomized or pseudorandomizedchanges to content of the first original data object.
 3. The method ofclaim 1, wherein the transformation function is a one-way function. 4.The method of claim 1, wherein the first transformed data objectincludes new content that is generated by applying imperceptible changesto content of the first original data object.
 5. The method of claim 1,wherein the first original data object includes at least one of: imagefile content or video file content, and wherein generating the firsttransformed data object includes applying changes to at least one pixelof the at least one of: the image file content or the video filecontent.
 6. The method of claim 1, wherein the first original dataobject includes sound file content, and wherein generating the firsttransformed data object includes applying audible changes to the soundfile content.
 7. The method of claim 1, wherein the first original dataobject includes document file content, and wherein generating the firsttransformed data object includes applying changes to at least one of:spacing, punctuation, or type-face of the document file content.
 8. Themethod of claim 1, further comprising: receiving an access historyrequest from a verifying entity via the network that indicates the firstoriginal data object and includes the first transformed data object;generating a second at least one read request for transmission to atleast one storage unit indicating the plurality of encoded original dataslices associated with the first original data object; generating asecond regenerated data object by utilizing the decoding scheme on theplurality of encoded original data slices; generating access historydata based on comparing the first transformed data object received fromthe verifying entity to the second regenerated data object, wherein theaccess history data indicates the first entity identifier associatedwith the first requesting entity; and transmitting the first entityidentifier to the verifying entity via the network.
 9. The method ofclaim 1, further comprising: generating a plurality of encodedtransformed data slices by applying an encoding scheme to the firsttransformed data object; and generating a plurality of write requestsfor transmission to a first plurality of storage units via the network,wherein each of the plurality of write requests includes at least one ofthe plurality of encoded transformed data slices for storage.
 10. Themethod of claim 9, further comprising generating a plurality of deleterequests corresponding to each of the plurality of encoded original dataslices associated with the first original data object for transmissionto a second plurality of storage units via the network, wherein each ofthe plurality of delete requests indicate one of the plurality ofencoded original data slices for removal from a corresponding one of thesecond plurality of storage units.
 11. The method of claim 9, whereineach of the plurality of write requests includes a request to replaceone of the plurality of encoded original data slices with a one of theplurality of encoded transformed data slices.
 12. The method of claim 9,further comprising: receiving an access history request from a verifyingentity via the network that indicates the first original data object;generating a second at least one read request for transmission to atleast one of the first plurality of storage units indicating theplurality of encoded transformed data slices associated with the firsttransformed data object; generating a regenerated transformed dataobject by utilizing the decoding scheme on the plurality of encodedtransformed data slices; generating access history data based oncomparing the first original data object to the regenerated transformeddata object, wherein the access history data indicates the first entityidentifier associated with the first requesting entity; and transmittingthe first entity identifier to the verifying entity via the network. 13.The method of claim 1, further comprising: receiving a second originaldata object from a second requesting entity for storage; generating asecond transformed data object by utilizing the transformation functionon the second original data object based on a second entity identifierassociated with the second requesting entity; generating a plurality ofencoded transformed data slices by applying an encoding scheme to thesecond transformed data object; and generating a plurality of writerequests for transmission to a plurality of storage units via thenetwork, wherein each of the plurality of write requests includes atleast one of the plurality of encoded transformed data slices forstorage.
 14. A processing system of a dispersed storage and task (DST)processing unit comprises: at least one processor; a memory that storesoperational instructions, that when executed by the at least oneprocessor cause the processing system to: receive an access request froma first requesting entity via a network indicating a first original dataobject; generate a first at least one read request for transmission toat least one storage unit to retrieve a plurality of encoded originaldata slices associated with the first original data object; generate afirst regenerated original data object by utilizing a decoding scheme onthe plurality of encoded original data slices; and generate a firsttransformed data object for transmission to the first requesting entityvia the network by utilizing a transformation function on the firstregenerated original data object based on a first entity identifierassociated with the first requesting entity.
 15. The processing systemof claim 14, wherein the transformation function includes inserting oneof: randomized or pseudorandomized changes to content of the firstoriginal data object.
 16. The processing system of claim 14, wherein theoperational instructions, when executed by the at least one processor,further cause the processing system to: receive an access historyrequest from a verifying entity via the network that indicates the firstoriginal data object and includes the first transformed data object;generate a second at least one read request for transmission to at leastone storage unit indicating the plurality of encoded original dataslices associated with the first original data object; generate a secondregenerated data object by utilizing the decoding scheme on theplurality of encoded original data slices; generate access history databased on comparing the first transformed data object received from theverifying entity to the second regenerated data object, wherein theaccess history data indicates the first entity identifier associatedwith the first requesting entity; and transmit the first entityidentifier to the verifying entity via the network.
 17. The processingsystem of claim 14, wherein the operational instructions, when executedby the at least one processor, further cause the processing system to:generate a plurality of encoded transformed data slices by applying anencoding scheme to the first transformed data object; and generate aplurality of write requests for transmission to a first plurality ofstorage units via the network, wherein each of the plurality of writerequests includes at least one of the plurality of encoded transformeddata slices for storage.
 18. The processing system of claim 17, whereinthe operational instructions, when executed by the at least oneprocessor, further cause the processing system to: receive an accesshistory request from a verifying entity via the network that indicatesthe first original data object; generate a second at least one readrequest for transmission to at least one of the first plurality ofstorage units indicating the plurality of encoded transformed dataslices associated with the first transformed data object; generate aregenerated transformed data object by utilizing the decoding scheme onthe plurality of encoded transformed data slices; generate accesshistory data based on comparing the first original data object to theregenerated transformed data object, wherein the access history dataindicates the first entity identifier associated with the firstrequesting entity; and transmit the first entity identifier to theverifying entity via the network.
 19. The processing system of claim 14,wherein the operational instructions, when executed by the at least oneprocessor, further cause the processing system to: receive a secondoriginal data object from a second requesting entity for storage;generate a second transformed data object by utilizing thetransformation function on the second original data object based on asecond entity identifier associated with the second requesting entity;generate a plurality of encoded transformed data slices by applying anencoding scheme to the second transformed data object; and generate aplurality of write requests for transmission to a plurality of storageunits via the network, wherein each of the plurality of write requestsincludes at least one of the plurality of encoded transformed dataslices for storage.
 20. A non-transitory computer readable storagemedium comprises: at least one memory section that stores operationalinstructions that, when executed by a processing system of a dispersedstorage network (DSN) that includes a processor and a memory, causes theprocessing system to: receive an access request from a first requestingentity via a network indicating a first original data object; generate afirst at least one read request for transmission via the network to atleast one storage unit of the DSN to retrieve a plurality of encodedoriginal data slices associated with the first original data object;generate a first regenerated original data object by utilizing adecoding scheme on the plurality of encoded original data slices; andgenerate a first transformed data object for transmission to the firstrequesting entity via the network by utilizing a transformation functionon the first regenerated original data object based on a first entityidentifier associated with the first requesting entity.